#include "data.h"
#include "utils.h"
#include "image.h"
#include "opencl.h"

#include <stdio.h>
#include <stdlib.h>
#include <string.h>

pthread_mutex_t mutex = PTHREAD_MUTEX_INITIALIZER;
#define class temp
#define new new_temp

list *get_paths(char *filename)
{
    if (filename) filename[strcspn(filename, "\n\r")] = 0;
    char *pos;
    if ((pos=strchr(filename, '\r')) != NULL) *pos = '\0';
    if ((pos=strchr(filename, '\n')) != NULL) *pos = '\0';
    char *path;
	FILE *file = fopen(filename, "r");
	if(!file) file_error(filename);
	list *lines = make_list();
	while((path=fgetl(file))){
            if (path) path[strcspn(path, "\n\r")] = 0;
            list_insert(lines, path);
	}
	fclose(file);
	return lines;
}

/*
char **get_random_paths_indexes(char **paths, int n, int m, int *indexes)
{
	char **random_paths = calloc(n, sizeof(char*));
	int i;
	pthread_mutex_lock(&mutex);
	for(i = 0; i < n; ++i){
		int index = rand()%m;
		indexes[i] = index;
		random_paths[i] = paths[index];
		//if(i == 0) printf("%s\n", paths[index]);
	}
	pthread_mutex_unlock(&mutex);
	return random_paths;
}
*/

char **get_random_paths(char **paths, int n, int m)
{
    pthread_mutex_lock(&mutex);
    char **random_paths = (char**)calloc(n, sizeof(char*));
    int i;
    for(i = 0; i < n; ++i){
        int index = rand()%m;
        random_paths[i] = paths[index];
        //if(i == 0) printf("%s\n", paths[index]);
    }
    pthread_mutex_unlock(&mutex);
    return random_paths;
}

char **find_replace_paths(char **paths, int n, char *find, char *replace)
{
	char **replace_paths = (char**)calloc(n, sizeof(char*));
	int i;
	for(i = 0; i < n; ++i){
		char replaced[4096];
		find_replace(paths[i], find, replace, replaced);
		replace_paths[i] = copy_string(replaced);
	}
	return replace_paths;
}

matrix load_image_paths_gray(char **paths, int n, int w, int h)
{
	int i;
	matrix X;
	X.rows = n;
	X.vals = (float**)calloc(X.rows, sizeof(float*));
	X.cols = 0;

	for(i = 0; i < n; ++i){
		image im = load_image(paths[i], w, h, 3);

		image gray = grayscale_image(im);
		free_image(im);
		im = gray;

		X.vals[i] = im.data;
		X.cols = im.h*im.w*im.c;
	}
	return X;
}

matrix load_image_paths(char **paths, int n, int w, int h)
{
	int i;
	matrix X;
	X.rows = n;
	X.vals = (float**)calloc(X.rows, sizeof(float*));
	X.cols = 0;

	for(i = 0; i < n; ++i){
		image im = load_image_color(paths[i], w, h);
		X.vals[i] = im.data;
		X.cols = im.h*im.w*im.c;
	}
	return X;
}

matrix load_image_augment_paths(char **paths, int n, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure, int center)
{
	int i;
	matrix X;
	X.rows = n;
	X.vals = (float**)calloc(X.rows, sizeof(float*));
	X.cols = 0;

	for(i = 0; i < n; ++i){
		image im = load_image_color(paths[i], 0, 0);
		image crop;
		if(center){
			crop = center_crop_image(im, size, size);
		} else {
			crop = random_augment_image(im, angle, aspect, min, max, size, size);
		}
		int flip = rand()%2;
		if (flip) flip_image(crop);
		random_distort_image(crop, hue, saturation, exposure);

		/*
		show_image(im, "orig");
		show_image(crop, "crop");
		cvWaitKey(0);
		*/
		//grayscale_image_3c(crop);
		free_image(im);
		X.vals[i] = crop.data;
		X.cols = crop.h*crop.w*crop.c;
	}
	return X;
}


box_label *read_boxes(char *filename, int *n)
{
    if (filename) filename[strcspn(filename, "\n\r")] = 0;
    char *pos;
    if ((pos=strchr(filename, '\r')) != NULL) *pos = '\0';
    if ((pos=strchr(filename, '\n')) != NULL) *pos = '\0';
	FILE *file = fopen(filename, "r");
	if(!file) file_error(filename);
	float x, y, h, w;
	int id;
	int count = 0;
	int size = 64;
	box_label *boxes = (box_label*)calloc(size, sizeof(box_label));
	while(fscanf(file, "%d %f %f %f %f", &id, &x, &y, &w, &h) == 5){
		if(count == size) {
			size = size * 2;
			boxes = (box_label*)realloc(boxes, size*sizeof(box_label));
		}
		boxes[count].id = id;
		boxes[count].x = x;
		boxes[count].y = y;
		boxes[count].h = h;
		boxes[count].w = w;
		boxes[count].left   = x - w/2;
		boxes[count].right  = x + w/2;
		boxes[count].top    = y - h/2;
		boxes[count].bottom = y + h/2;
		++count;
	}
	fclose(file);
	*n = count;
	return boxes;
}

void randomize_boxes(box_label *b, int n)
{
	int i;
	for(i = 0; i < n; ++i){
		box_label swap = b[i];
		int index = rand()%n;
		b[i] = b[index];
		b[index] = swap;
	}
}

void correct_boxes(box_label *boxes, int n, float dx, float dy, float sx, float sy, int flip)
{
	int i;
	for(i = 0; i < n; ++i){
		if(boxes[i].x == 0 && boxes[i].y == 0) {
			boxes[i].x = 999999;
			boxes[i].y = 999999;
			boxes[i].w = 999999;
			boxes[i].h = 999999;
			continue;
		}
		boxes[i].left   = boxes[i].left  * sx - dx;
		boxes[i].right  = boxes[i].right * sx - dx;
		boxes[i].top    = boxes[i].top   * sy - dy;
		boxes[i].bottom = boxes[i].bottom* sy - dy;

		if(flip){
			float swap = boxes[i].left;
			boxes[i].left = 1. - boxes[i].right;
			boxes[i].right = 1. - swap;
		}

		boxes[i].left =  constrain(0, 1, boxes[i].left);
		boxes[i].right = constrain(0, 1, boxes[i].right);
		boxes[i].top =   constrain(0, 1, boxes[i].top);
		boxes[i].bottom =   constrain(0, 1, boxes[i].bottom);

		boxes[i].x = (boxes[i].left+boxes[i].right)/2;
		boxes[i].y = (boxes[i].top+boxes[i].bottom)/2;
		boxes[i].w = (boxes[i].right - boxes[i].left);
		boxes[i].h = (boxes[i].bottom - boxes[i].top);

		boxes[i].w = constrain(0, 1, boxes[i].w);
		boxes[i].h = constrain(0, 1, boxes[i].h);
	}
}

void fill_truth_swag(char *path, float *truth, int classes, int flip, float dx, float dy, float sx, float sy)
{
	char labelpath[4096];
	find_replace(path, "images", "labels", labelpath);
	find_replace(labelpath, "JPEGImages", "labels", labelpath);
	find_replace(labelpath, ".jpg", ".txt", labelpath);
	find_replace(labelpath, ".JPG", ".txt", labelpath);
	find_replace(labelpath, ".JPEG", ".txt", labelpath);

	int count = 0;
	box_label *boxes = read_boxes(labelpath, &count);
	randomize_boxes(boxes, count);
	correct_boxes(boxes, count, dx, dy, sx, sy, flip);
	float x,y,w,h;
	int id;
	int i;

	for (i = 0; i < count && i < 90; ++i) {
		x =  boxes[i].x;
		y =  boxes[i].y;
		w =  boxes[i].w;
		h =  boxes[i].h;
		id = boxes[i].id;

		if (w < .0 || h < .0) continue;

		int index = (4+classes) * i;

		truth[index++] = x;
		truth[index++] = y;
		truth[index++] = w;
		truth[index++] = h;

		if (id < classes) truth[index+id] = 1;
	}
	free(boxes);
}

void fill_truth_region(char *path, float *truth, int classes, int num_boxes, int flip, float dx, float dy, float sx, float sy)
{
	char labelpath[4096];
	find_replace(path, "images", "labels", labelpath);
	find_replace(labelpath, "JPEGImages", "labels", labelpath);

	find_replace(labelpath, ".jpg", ".txt", labelpath);
	find_replace(labelpath, ".png", ".txt", labelpath);
	find_replace(labelpath, ".JPG", ".txt", labelpath);
	find_replace(labelpath, ".JPEG", ".txt", labelpath);
	int count = 0;
	box_label *boxes = read_boxes(labelpath, &count);
	randomize_boxes(boxes, count);
	correct_boxes(boxes, count, dx, dy, sx, sy, flip);
	float x,y,w,h;
	int id;
	int i;

	for (i = 0; i < count; ++i) {
		x =  boxes[i].x;
		y =  boxes[i].y;
		w =  boxes[i].w;
		h =  boxes[i].h;
		id = boxes[i].id;

		if (w < .005 || h < .005) continue;

		int col = (int)(x*num_boxes);
		int row = (int)(y*num_boxes);

		x = x*num_boxes - col;
		y = y*num_boxes - row;

		int index = (col+row*num_boxes)*(5+classes);
		if (truth[index]) continue;
		truth[index++] = 1;

		if (id < classes) truth[index+id] = 1;
		index += classes;

		truth[index++] = x;
		truth[index++] = y;
		truth[index++] = w;
		truth[index++] = h;
	}
	free(boxes);
}

void load_rle(image im, int *rle, int n)
{
	int count = 0;
	int curr = 0;
	int i,j;
	for(i = 0; i < n; ++i){
		for(j = 0; j < rle[i]; ++j){
			im.data[count++] = curr;
		}
		curr = 1 - curr;
	}
	for(; count < im.h*im.w*im.c; ++count){
		im.data[count] = curr;
	}
}

void or_image(image src, image dest, int c)
{
	int i;
	for(i = 0; i < src.w*src.h; ++i){
		if(src.data[i]) dest.data[dest.w*dest.h*c + i] = 1;
	}
}

void exclusive_image(image src)
{
	int k, j, i;
	int s = src.w*src.h;
	for(k = 0; k < src.c-1; ++k){
		for(i = 0; i < s; ++i){
			if (src.data[k*s + i]){
				for(j = k+1; j < src.c; ++j){
					src.data[j*s + i] = 0;
				}
			}
		}
	}
}

box bound_image(image im)
{
	int x,y;
	int minx = im.w;
	int miny = im.h;
	int maxx = 0;
	int maxy = 0;
	for(y = 0; y < im.h; ++y){
		for(x = 0; x < im.w; ++x){
			if(im.data[y*im.w + x]){
				minx = (x < minx) ? x : minx;
				miny = (y < miny) ? y : miny;
				maxx = (x > maxx) ? x : maxx;
				maxy = (y > maxy) ? y : maxy;
			}
		}
	}
	box b = {minx, miny, maxx-minx + 1, maxy-miny + 1};
	//printf("%f %f %f %f\n", b.x, b.y, b.w, b.h);
	return b;
}

void fill_truth_iseg(char *path, int num_boxes, float *truth, int classes, int w, int h, augment_args aug, int flip, int mw, int mh)
{
	char labelpath[4096];
	find_replace(path, "images", "mask", labelpath);
	find_replace(labelpath, "JPEGImages", "mask", labelpath);
	find_replace(labelpath, ".jpg", ".txt", labelpath);
	find_replace(labelpath, ".JPG", ".txt", labelpath);
	find_replace(labelpath, ".JPEG", ".txt", labelpath);
	FILE *file = fopen(labelpath, "r");
	if(!file) file_error(labelpath);
	char buff[32788];
	int id;
	int i = 0;
	int j;
	image part = make_image(w, h, 1);
	while((fscanf(file, "%d %s", &id, buff) == 2) && i < num_boxes){
		int n = 0;
		int *rle = read_intlist(buff, &n, 0);
		load_rle(part, rle, n);
		image sized = rotate_crop_image(part, aug.rad, aug.scale, aug.w, aug.h, aug.dx, aug.dy, aug.aspect);
		if(flip) flip_image(sized);

		image mask = resize_image(sized, mw, mh);
		truth[i*(mw*mh+1)] = id;
		for(j = 0; j < mw*mh; ++j){
			truth[i*(mw*mh + 1) + 1 + j] = mask.data[j];
		}
		++i;

		free_image(mask);
		free_image(sized);
		free(rle);
	}
	if(i < num_boxes) truth[i*(mw*mh+1)] = -1;
	fclose(file);
	free_image(part);
}

void fill_truth_mask(char *path, int num_boxes, float *truth, int classes, int w, int h, augment_args aug, int flip, int mw, int mh)
{
	char labelpath[4096];
	find_replace(path, "images", "mask", labelpath);
	find_replace(labelpath, "JPEGImages", "mask", labelpath);
	find_replace(labelpath, ".jpg", ".txt", labelpath);
	find_replace(labelpath, ".JPG", ".txt", labelpath);
	find_replace(labelpath, ".JPEG", ".txt", labelpath);
	FILE *file = fopen(labelpath, "r");
	if(!file) file_error(labelpath);
	char buff[32788];
	int id;
	int i = 0;
	image part = make_image(w, h, 1);
	while((fscanf(file, "%d %s", &id, buff) == 2) && i < num_boxes){
		int n = 0;
		int *rle = read_intlist(buff, &n, 0);
		load_rle(part, rle, n);
		image sized = rotate_crop_image(part, aug.rad, aug.scale, aug.w, aug.h, aug.dx, aug.dy, aug.aspect);
		if(flip) flip_image(sized);
		box b = bound_image(sized);
		if(b.w > 0){
			image crop = crop_image(sized, b.x, b.y, b.w, b.h);
			image mask = resize_image(crop, mw, mh);
			truth[i*(4 + mw*mh + 1) + 0] = (b.x + b.w/2.)/sized.w;
			truth[i*(4 + mw*mh + 1) + 1] = (b.y + b.h/2.)/sized.h;
			truth[i*(4 + mw*mh + 1) + 2] = b.w/sized.w;
			truth[i*(4 + mw*mh + 1) + 3] = b.h/sized.h;
			int j;
			for(j = 0; j < mw*mh; ++j){
				truth[i*(4 + mw*mh + 1) + 4 + j] = mask.data[j];
			}
			truth[i*(4 + mw*mh + 1) + 4 + mw*mh] = id;
			free_image(crop);
			free_image(mask);
			++i;
		}
		free_image(sized);
		free(rle);
	}
	fclose(file);
	free_image(part);
}


void fill_truth_detection(char *path, int num_boxes, float *truth, int classes, int flip, float dx, float dy, float sx, float sy)
{
	char labelpath[4096];
	find_replace(path, "images", "labels", labelpath);
	find_replace(labelpath, "JPEGImages", "labels", labelpath);

	find_replace(labelpath, "raw", "labels", labelpath);
	find_replace(labelpath, ".jpg", ".txt", labelpath);
	find_replace(labelpath, ".png", ".txt", labelpath);
	find_replace(labelpath, ".JPG", ".txt", labelpath);
	find_replace(labelpath, ".JPEG", ".txt", labelpath);
	int count = 0;
	box_label *boxes = read_boxes(labelpath, &count);
	randomize_boxes(boxes, count);
	correct_boxes(boxes, count, dx, dy, sx, sy, flip);
	if(count > num_boxes) count = num_boxes;
	float x,y,w,h;
	int id;
	int i;
	int sub = 0;

	for (i = 0; i < count; ++i) {
		x =  boxes[i].x;
		y =  boxes[i].y;
		w =  boxes[i].w;
		h =  boxes[i].h;
		id = boxes[i].id;

		if ((w < .001 || h < .001)) {
			++sub;
			continue;
		}

		truth[(i-sub)*5+0] = x;
		truth[(i-sub)*5+1] = y;
		truth[(i-sub)*5+2] = w;
		truth[(i-sub)*5+3] = h;
		truth[(i-sub)*5+4] = id;
	}
	free(boxes);
}

#define NUMCHARS 37

void print_letters(float *pred, int n)
{
	int i;
	for(i = 0; i < n; ++i){
		int index = max_index(pred+i*NUMCHARS, NUMCHARS);
		printf("%c", int_to_alphanum(index));
	}
	printf("\n");
}

void fill_truth_captcha(char *path, int n, float *truth)
{
	char *begin = strrchr(path, '/');
	++begin;
	int i;
	for(i = 0; i < strlen(begin) && i < n && begin[i] != '.'; ++i){
		int index = alphanum_to_int(begin[i]);
		if(index > 35) printf("Bad %c\n", begin[i]);
		truth[i*NUMCHARS+index] = 1;
	}
	for(;i < n; ++i){
		truth[i*NUMCHARS + NUMCHARS-1] = 1;
	}
}

data load_data_captcha(char **paths, int n, int m, int k, int w, int h)
{
	if(m) paths = get_random_paths(paths, n, m);
	data d = {0};
	d.shallow = 0;
	d.X = load_image_paths(paths, n, w, h);
	d.y = make_matrix(n, k*NUMCHARS);
	int i;
	for(i = 0; i < n; ++i){
		fill_truth_captcha(paths[i], k, d.y.vals[i]);
	}
	if(m) free(paths);
	return d;
}

data load_data_captcha_encode(char **paths, int n, int m, int w, int h)
{
	if(m) paths = get_random_paths(paths, n, m);
	data d = {0};
	d.shallow = 0;
	d.X = load_image_paths(paths, n, w, h);
	d.X.cols = 17100;
	d.y = d.X;
	if(m) free(paths);
	return d;
}

void fill_truth(char *path, char **labels, int k, float *truth)
{
	int i;
	memset(truth, 0, k*sizeof(float));
	int count = 0;
	for(i = 0; i < k; ++i){
		if(strstr(path, labels[i])){
			truth[i] = 1;
			++count;
			//printf("%s %s %d\n", path, labels[i], i);
		}
	}
	if(count != 1 && (k != 1 || count != 0)) printf("Too many or too few labels: %d, %s\n", count, path);
}

void fill_hierarchy(float *truth, int k, tree *hierarchy)
{
	int j;
	for(j = 0; j < k; ++j){
		if(truth[j]){
			int parent = hierarchy->parent[j];
			while(parent >= 0){
				truth[parent] = 1;
				parent = hierarchy->parent[parent];
			}
		}
	}
	int i;
	int count = 0;
	for(j = 0; j < hierarchy->groups; ++j){
		//printf("%d\n", count);
		int mask = 1;
		for(i = 0; i < hierarchy->group_size[j]; ++i){
			if(truth[count + i]){
				mask = 0;
				break;
			}
		}
		if (mask) {
			for(i = 0; i < hierarchy->group_size[j]; ++i){
				truth[count + i] = SECRET_NUM;
			}
		}
		count += hierarchy->group_size[j];
	}
}

matrix load_regression_labels_paths(char **paths, int n, int k)
{
	matrix y = make_matrix(n, k);
	int i,j;
	for(i = 0; i < n; ++i){
		char labelpath[4096];
		find_replace(paths[i], "images", "labels", labelpath);
		find_replace(labelpath, "JPEGImages", "labels", labelpath);
		find_replace(labelpath, ".BMP", ".txt", labelpath);
		find_replace(labelpath, ".JPEG", ".txt", labelpath);
		find_replace(labelpath, ".JPG", ".txt", labelpath);
		find_replace(labelpath, ".JPeG", ".txt", labelpath);
		find_replace(labelpath, ".Jpeg", ".txt", labelpath);
		find_replace(labelpath, ".PNG", ".txt", labelpath);
		find_replace(labelpath, ".TIF", ".txt", labelpath);
		find_replace(labelpath, ".bmp", ".txt", labelpath);
		find_replace(labelpath, ".jpeg", ".txt", labelpath);
		find_replace(labelpath, ".jpg", ".txt", labelpath);
		find_replace(labelpath, ".png", ".txt", labelpath);
		find_replace(labelpath, ".tif", ".txt", labelpath);

		FILE *file = fopen(labelpath, "r");
		for(j = 0; j < k; ++j){
			fscanf(file, "%f", &(y.vals[i][j]));
		}
		fclose(file);
	}
	return y;
}

matrix load_labels_paths(char **paths, int n, char **labels, int k, tree *hierarchy)
{
	matrix y = make_matrix(n, k);
	int i;
	for(i = 0; i < n && labels; ++i){
		fill_truth(paths[i], labels, k, y.vals[i]);
		if(hierarchy){
			fill_hierarchy(y.vals[i], k, hierarchy);
		}
	}
	return y;
}

matrix load_tags_paths(char **paths, int n, int k)
{
	matrix y = make_matrix(n, k);
	int i;
	//int count = 0;
	for(i = 0; i < n; ++i){
		char label[4096];
		find_replace(paths[i], "images", "labels", label);
		find_replace(label, ".jpg", ".txt", label);
		FILE *file = fopen(label, "r");
		if (!file) continue;
		//++count;
		int tag;
		while(fscanf(file, "%d", &tag) == 1){
			if(tag < k){
				y.vals[i][tag] = 1;
			}
		}
		fclose(file);
	}
	//printf("%d/%d\n", count, n);
	return y;
}

char **get_labels(char *filename)
{
	list *plist = get_paths(filename);
	char **labels = (char **)list_to_array(plist);
	free_list(plist);
	return labels;
}

void free_data(data d)
{
	if(!d.shallow){
		free_matrix(d.X);
		free_matrix(d.y);
	}else{
		free(d.X.vals);
		free(d.y.vals);
	}
}

image get_segmentation_image(char *path, int w, int h, int classes)
{
	char labelpath[4096];
	find_replace(path, "images", "mask", labelpath);
	find_replace(labelpath, "JPEGImages", "mask", labelpath);
	find_replace(labelpath, ".jpg", ".txt", labelpath);
	find_replace(labelpath, ".JPG", ".txt", labelpath);
	find_replace(labelpath, ".JPEG", ".txt", labelpath);
	image mask = make_image(w, h, classes);
	FILE *file = fopen(labelpath, "r");
	if(!file) file_error(labelpath);
	char buff[32788];
	int id;
	image part = make_image(w, h, 1);
	while(fscanf(file, "%d %s", &id, buff) == 2){
		int n = 0;
		int *rle = read_intlist(buff, &n, 0);
		load_rle(part, rle, n);
		or_image(part, mask, id);
		free(rle);
	}
	//exclusive_image(mask);
	fclose(file);
	free_image(part);
	return mask;
}

image get_segmentation_image2(char *path, int w, int h, int classes)
{
	char labelpath[4096];
	find_replace(path, "images", "mask", labelpath);
	find_replace(labelpath, "JPEGImages", "mask", labelpath);
	find_replace(labelpath, ".jpg", ".txt", labelpath);
	find_replace(labelpath, ".JPG", ".txt", labelpath);
	find_replace(labelpath, ".JPEG", ".txt", labelpath);
	image mask = make_image(w, h, classes+1);
	int i;
	for(i = 0; i < w*h; ++i){
		mask.data[w*h*classes + i] = 1;
	}
	FILE *file = fopen(labelpath, "r");
	if(!file) file_error(labelpath);
	char buff[32788];
	int id;
	image part = make_image(w, h, 1);
	while(fscanf(file, "%d %s", &id, buff) == 2){
		int n = 0;
		int *rle = read_intlist(buff, &n, 0);
		load_rle(part, rle, n);
		or_image(part, mask, id);
		for(i = 0; i < w*h; ++i){
			if(part.data[i]) mask.data[w*h*classes + i] = 0;
		}
		free(rle);
	}
	//exclusive_image(mask);
	fclose(file);
	free_image(part);
	return mask;
}

data load_data_seg(int n, char **paths, int m, int w, int h, int classes, int min, int max, float angle, float aspect, float hue, float saturation, float exposure, int div)
{
	char **random_paths = get_random_paths(paths, n, m);
	int i;
	data d = {0};
	d.shallow = 0;

	d.X.rows = n;
	d.X.vals = (float**)calloc(d.X.rows, sizeof(float*));
	d.X.cols = h*w*3;


	d.y.rows = n;
	d.y.cols = h*w*classes/div/div;
	d.y.vals = (float**)calloc(d.X.rows, sizeof(float*));

	for(i = 0; i < n; ++i){
		image orig = load_image_color(random_paths[i], 0, 0);
		augment_args a = random_augment_args(orig, angle, aspect, min, max, w, h);
		image sized = rotate_crop_image(orig, a.rad, a.scale, a.w, a.h, a.dx, a.dy, a.aspect);

		int flip = rand()%2;
		if(flip) flip_image(sized);
		random_distort_image(sized, hue, saturation, exposure);
		d.X.vals[i] = sized.data;

		image mask = get_segmentation_image(random_paths[i], orig.w, orig.h, classes);
		//image mask = make_image(orig.w, orig.h, classes+1);
		image sized_m = rotate_crop_image(mask, a.rad, a.scale/div, a.w/div, a.h/div, a.dx/div, a.dy/div, a.aspect);

		if(flip) flip_image(sized_m);
		d.y.vals[i] = sized_m.data;

		free_image(orig);
		free_image(mask);

		/*
		   image rgb = mask_to_rgb(sized_m, classes);
		   show_image(rgb, "part");
		   show_image(sized, "orig");
		   cvWaitKey(0);
		   free_image(rgb);
		 */
	}
	free(random_paths);
	return d;
}

data load_data_iseg(int n, char **paths, int m, int w, int h, int classes, int boxes, int div, int min, int max, float angle, float aspect, float hue, float saturation, float exposure)
{
	char **random_paths = get_random_paths(paths, n, m);
	int i;
	data d = {0};
	d.shallow = 0;

	d.X.rows = n;
	d.X.vals = (float**)calloc(d.X.rows, sizeof(float*));
	d.X.cols = h*w*3;

	d.y = make_matrix(n, (((w/div)*(h/div))+1)*boxes);

	for(i = 0; i < n; ++i){
		image orig = load_image_color(random_paths[i], 0, 0);
		augment_args a = random_augment_args(orig, angle, aspect, min, max, w, h);
		image sized = rotate_crop_image(orig, a.rad, a.scale, a.w, a.h, a.dx, a.dy, a.aspect);

		int flip = rand()%2;
		if(flip) flip_image(sized);
		random_distort_image(sized, hue, saturation, exposure);
		d.X.vals[i] = sized.data;
		//show_image(sized, "image");

		fill_truth_iseg(random_paths[i], boxes, d.y.vals[i], classes, orig.w, orig.h, a, flip, w/div, h/div);

		free_image(orig);

		/*
		   image rgb = mask_to_rgb(sized_m, classes);
		   show_image(rgb, "part");
		   show_image(sized, "orig");
		   cvWaitKey(0);
		   free_image(rgb);
		 */
	}
	free(random_paths);
	return d;
}

data load_data_mask(int n, char **paths, int m, int w, int h, int classes, int boxes, int coords, int min, int max, float angle, float aspect, float hue, float saturation, float exposure)
{
	char **random_paths = get_random_paths(paths, n, m);
	int i;
	data d = {0};
	d.shallow = 0;

	d.X.rows = n;
	d.X.vals = (float**)calloc(d.X.rows, sizeof(float*));
	d.X.cols = h*w*3;

	d.y = make_matrix(n, (coords+1)*boxes);

	for(i = 0; i < n; ++i){
		image orig = load_image_color(random_paths[i], 0, 0);
		augment_args a = random_augment_args(orig, angle, aspect, min, max, w, h);
		image sized = rotate_crop_image(orig, a.rad, a.scale, a.w, a.h, a.dx, a.dy, a.aspect);

		int flip = rand()%2;
		if(flip) flip_image(sized);
		random_distort_image(sized, hue, saturation, exposure);
		d.X.vals[i] = sized.data;
		//show_image(sized, "image");

		fill_truth_mask(random_paths[i], boxes, d.y.vals[i], classes, orig.w, orig.h, a, flip, 14, 14);

		free_image(orig);

		/*
		   image rgb = mask_to_rgb(sized_m, classes);
		   show_image(rgb, "part");
		   show_image(sized, "orig");
		   cvWaitKey(0);
		   free_image(rgb);
		 */
	}
	free(random_paths);
	return d;
}

data load_data_region(int n, char **paths, int m, int w, int h, int size, int classes, float jitter, float hue, float saturation, float exposure)
{
	char **random_paths = get_random_paths(paths, n, m);
	int i;
	data d = {0};
	d.shallow = 0;

	d.X.rows = n;
	d.X.vals = (float**)calloc(d.X.rows, sizeof(float*));
	d.X.cols = h*w*3;


	int k = size*size*(5+classes);
	d.y = make_matrix(n, k);
	for(i = 0; i < n; ++i){
		image orig = load_image_color(random_paths[i], 0, 0);

		int oh = orig.h;
		int ow = orig.w;

		int dw = (ow*jitter);
		int dh = (oh*jitter);

		int pleft  = rand_uniform(-dw, dw);
		int pright = rand_uniform(-dw, dw);
		int ptop   = rand_uniform(-dh, dh);
		int pbot   = rand_uniform(-dh, dh);

		int swidth =  ow - pleft - pright;
		int sheight = oh - ptop - pbot;

		float sx = (float)swidth  / ow;
		float sy = (float)sheight / oh;

		int flip = rand()%2;
		image cropped = crop_image(orig, pleft, ptop, swidth, sheight);

		float dx = ((float)pleft/ow)/sx;
		float dy = ((float)ptop /oh)/sy;

		image sized = resize_image(cropped, w, h);
		if(flip) flip_image(sized);
		random_distort_image(sized, hue, saturation, exposure);
		d.X.vals[i] = sized.data;

		fill_truth_region(random_paths[i], d.y.vals[i], classes, size, flip, dx, dy, 1./sx, 1./sy);

		free_image(orig);
		free_image(cropped);
	}
	free(random_paths);
	return d;
}

data load_data_compare(int n, char **paths, int m, int classes, int w, int h)
{
	if(m) paths = get_random_paths(paths, 2*n, m);
	int i,j;
	data d = {0};
	d.shallow = 0;

	d.X.rows = n;
	d.X.vals = (float**)calloc(d.X.rows, sizeof(float*));
	d.X.cols = h*w*6;

	int k = 2*(classes);
	d.y = make_matrix(n, k);
	for(i = 0; i < n; ++i){
		image im1 = load_image_color(paths[i*2],   w, h);
		image im2 = load_image_color(paths[i*2+1], w, h);

		d.X.vals[i] = (float*)calloc(d.X.cols, sizeof(float));
		memcpy(d.X.vals[i],         im1.data, h*w*3*sizeof(float));
		memcpy(d.X.vals[i] + h*w*3, im2.data, h*w*3*sizeof(float));

		int id;
		float iou;

		char imlabel1[4096];
		char imlabel2[4096];
		find_replace(paths[i*2],   "imgs", "labels", imlabel1);
		find_replace(imlabel1, "jpg", "txt", imlabel1);
		FILE *fp1 = fopen(imlabel1, "r");

		while(fscanf(fp1, "%d %f", &id, &iou) == 2){
			if (d.y.vals[i][2*id] < iou) d.y.vals[i][2*id] = iou;
		}

		find_replace(paths[i*2+1], "imgs", "labels", imlabel2);
		find_replace(imlabel2, "jpg", "txt", imlabel2);
		FILE *fp2 = fopen(imlabel2, "r");

		while(fscanf(fp2, "%d %f", &id, &iou) == 2){
			if (d.y.vals[i][2*id + 1] < iou) d.y.vals[i][2*id + 1] = iou;
		}

		for (j = 0; j < classes; ++j){
			if (d.y.vals[i][2*j] > .5 &&  d.y.vals[i][2*j+1] < .5){
				d.y.vals[i][2*j] = 1;
				d.y.vals[i][2*j+1] = 0;
			} else if (d.y.vals[i][2*j] < .5 &&  d.y.vals[i][2*j+1] > .5){
				d.y.vals[i][2*j] = 0;
				d.y.vals[i][2*j+1] = 1;
			} else {
				d.y.vals[i][2*j]   = SECRET_NUM;
				d.y.vals[i][2*j+1] = SECRET_NUM;
			}
		}
		fclose(fp1);
		fclose(fp2);

		free_image(im1);
		free_image(im2);
	}
	if(m) free(paths);
	return d;
}

data load_data_swag(char **paths, int n, int classes, float jitter)
{
	int index = rand()%n;
	char *random_path = paths[index];

	image orig = load_image_color(random_path, 0, 0);
	int h = orig.h;
	int w = orig.w;

	data d = {0};
	d.shallow = 0;
	d.w = w;
	d.h = h;

	d.X.rows = 1;
	d.X.vals = (float**)calloc(d.X.rows, sizeof(float*));
	d.X.cols = h*w*3;

	int k = (4+classes)*90;
	d.y = make_matrix(1, k);

	int dw = w*jitter;
	int dh = h*jitter;

	int pleft  = rand_uniform(-dw, dw);
	int pright = rand_uniform(-dw, dw);
	int ptop   = rand_uniform(-dh, dh);
	int pbot   = rand_uniform(-dh, dh);

	int swidth =  w - pleft - pright;
	int sheight = h - ptop - pbot;

	float sx = (float)swidth  / w;
	float sy = (float)sheight / h;

	int flip = rand()%2;
	image cropped = crop_image(orig, pleft, ptop, swidth, sheight);

	float dx = ((float)pleft/w)/sx;
	float dy = ((float)ptop /h)/sy;

	image sized = resize_image(cropped, w, h);
	if(flip) flip_image(sized);
	d.X.vals[0] = sized.data;

	fill_truth_swag(random_path, d.y.vals[0], classes, flip, dx, dy, 1./sx, 1./sy);

	free_image(orig);
	free_image(cropped);

	return d;
}

data load_data_detection(int n, char **paths, int m, int w, int h, int boxes, int classes, float jitter, float hue, float saturation, float exposure)
{
	char **random_paths = get_random_paths(paths, n, m);
	int i;
	data d = {0};
	d.shallow = 0;

	d.X.rows = n;
	d.X.vals = (float**)calloc(d.X.rows, sizeof(float*));
	d.X.cols = h*w*3;

	d.y = make_matrix(n, 5*boxes);

	for(i = 0; i < n; ++i){
		image orig = load_image_color(random_paths[i], 0, 0);
		image sized = make_image(w, h, orig.c);
		fill_image(sized, .5);

		float dw = jitter * orig.w;
		float dh = jitter * orig.h;

		float new_ar = (orig.w + rand_uniform(-dw, dw)) / (orig.h + rand_uniform(-dh, dh));
		//float scale = rand_uniform(.25, 2);
		float scale = 1;

		float nw, nh;

		if(new_ar < 1){
			nh = scale * h;
			nw = nh * new_ar;
		} else {
			nw = scale * w;
			nh = nw / new_ar;
		}

		float dx = rand_uniform(0, w - nw);
		float dy = rand_uniform(0, h - nh);

		place_image(orig, nw, nh, dx, dy, sized);

		random_distort_image(sized, hue, saturation, exposure);

		int flip = rand()%2;
		if(flip) flip_image(sized);
		d.X.vals[i] = sized.data;

		fill_truth_detection(random_paths[i], boxes, d.y.vals[i], classes, flip, -dx/w, -dy/h, nw/w, nh/h);

		free_image(orig);
	}
	free(random_paths);
    return d;
}

void *load_thread(void *ptr)
{
	//printf("Loading data: %d\n", rand());
	load_args a = *(struct load_args*)ptr;
	if(a.exposure == 0) a.exposure = 1;
	if(a.saturation == 0) a.saturation = 1;
	if(a.aspect == 0) a.aspect = 1;

	if (a.type == OLD_CLASSIFICATION_DATA){
		*a.d = load_data_old(a.paths, a.n, a.m, a.labels, a.classes, a.w, a.h);
	} else if (a.type == REGRESSION_DATA){
		*a.d = load_data_regression(a.paths, a.n, a.m, a.classes, a.min, a.max, a.size, a.angle, a.aspect, a.hue, a.saturation, a.exposure);
	} else if (a.type == CLASSIFICATION_DATA){
		*a.d = load_data_augment(a.paths, a.n, a.m, a.labels, a.classes, a.hierarchy, a.min, a.max, a.size, a.angle, a.aspect, a.hue, a.saturation, a.exposure, a.center);
	} else if (a.type == SUPER_DATA){
		*a.d = load_data_super(a.paths, a.n, a.m, a.w, a.h, a.scale);
	} else if (a.type == WRITING_DATA){
		*a.d = load_data_writing(a.paths, a.n, a.m, a.w, a.h, a.out_w, a.out_h);
	} else if (a.type == ISEG_DATA){
		*a.d = load_data_iseg(a.n, a.paths, a.m, a.w, a.h, a.classes, a.num_boxes, a.scale, a.min, a.max, a.angle, a.aspect, a.hue, a.saturation, a.exposure);
	} else if (a.type == INSTANCE_DATA){
		*a.d = load_data_mask(a.n, a.paths, a.m, a.w, a.h, a.classes, a.num_boxes, a.coords, a.min, a.max, a.angle, a.aspect, a.hue, a.saturation, a.exposure);
	} else if (a.type == SEGMENTATION_DATA){
		*a.d = load_data_seg(a.n, a.paths, a.m, a.w, a.h, a.classes, a.min, a.max, a.angle, a.aspect, a.hue, a.saturation, a.exposure, a.scale);
	} else if (a.type == REGION_DATA){
		*a.d = load_data_region(a.n, a.paths, a.m, a.w, a.h, a.num_boxes, a.classes, a.jitter, a.hue, a.saturation, a.exposure);
	} else if (a.type == DETECTION_DATA){
		*a.d = load_data_detection(a.n, a.paths, a.m, a.w, a.h, a.num_boxes, a.classes, a.jitter, a.hue, a.saturation, a.exposure);
	} else if (a.type == SWAG_DATA){
		*a.d = load_data_swag(a.paths, a.n, a.classes, a.jitter);
	} else if (a.type == COMPARE_DATA){
		*a.d = load_data_compare(a.n, a.paths, a.m, a.classes, a.w, a.h);
	} else if (a.type == IMAGE_DATA){
		*(a.im) = load_image_color(a.path, 0, 0);
		*(a.resized) = resize_image(*(a.im), a.w, a.h);
	} else if (a.type == LETTERBOX_DATA){
		*(a.im) = load_image_color(a.path, 0, 0);
		*(a.resized) = letterbox_image(*(a.im), a.w, a.h);
	} else if (a.type == TAG_DATA){
		*a.d = load_data_tag(a.paths, a.n, a.m, a.classes, a.min, a.max, a.size, a.angle, a.aspect, a.hue, a.saturation, a.exposure);
	}
	free(ptr);
	return 0;
}

pthread_t load_data_in_thread(load_args args)
{
	pthread_t thread;
	struct load_args *ptr = (load_args*)calloc(1, sizeof(struct load_args));
	*ptr = args;
	if(pthread_create(&thread, 0, load_thread, ptr)) error("Thread creation failed");
	return thread;
}

void *load_threads(void *ptr)
{
	int i;
	load_args args = *(load_args *)ptr;
	if (args.threads == 0) args.threads = 1;
	data *out = args.d;
	int total = args.n;
	free(ptr);
	data *buffers = (data*)calloc(args.threads, sizeof(data));
	pthread_t *threads = (pthread_t*)calloc(args.threads, sizeof(pthread_t));
	for(i = 0; i < args.threads; ++i){
		args.d = buffers + i;
		args.n = (i+1) * total/args.threads - i * total/args.threads;
		threads[i] = load_data_in_thread(args);
	}
	for(i = 0; i < args.threads; ++i){
		pthread_join(threads[i], 0);
	}
	*out = concat_datas(buffers, args.threads);
	out->shallow = 0;
	for(i = 0; i < args.threads; ++i){
		buffers[i].shallow = 1;
		free_data(buffers[i]);
	}
	free(buffers);
	free(threads);
	return 0;
}

void load_data_blocking(load_args args)
{
	struct load_args *ptr = (load_args*)calloc(1, sizeof(struct load_args));
	*ptr = args;
	load_thread(ptr);
}

pthread_t load_data(load_args args)
{
	pthread_t thread;
	struct load_args *ptr = (load_args*)calloc(1, sizeof(struct load_args));
	*ptr = args;
	if(pthread_create(&thread, 0, load_threads, ptr)) error("Thread creation failed");
	return thread;
}

data load_data_writing(char **paths, int n, int m, int w, int h, int out_w, int out_h)
{
	if(m) paths = get_random_paths(paths, n, m);
	char **replace_paths = find_replace_paths(paths, n, ".png", "-label.png");
	data d = {0};
	d.shallow = 0;
	d.X = load_image_paths(paths, n, w, h);
	d.y = load_image_paths_gray(replace_paths, n, out_w, out_h);
	if(m) free(paths);
	int i;
	for(i = 0; i < n; ++i) free(replace_paths[i]);
	free(replace_paths);
	return d;
}

data load_data_old(char **paths, int n, int m, char **labels, int k, int w, int h)
{
	if(m) paths = get_random_paths(paths, n, m);
	data d = {0};
	d.shallow = 0;
	d.X = load_image_paths(paths, n, w, h);
	d.y = load_labels_paths(paths, n, labels, k, 0);
	if(m) free(paths);
	return d;
}

/*
   data load_data_study(char **paths, int n, int m, char **labels, int k, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
   {
   data d = {0};
   d.indexes = calloc(n, sizeof(int));
   if(m) paths = get_random_paths_indexes(paths, n, m, d.indexes);
   d.shallow = 0;
   d.X = load_image_augment_paths(paths, n, min, max, size, angle, aspect, hue, saturation, exposure);
   d.y = load_labels_paths(paths, n, labels, k);
   if(m) free(paths);
   return d;
   }
 */

data load_data_super(char **paths, int n, int m, int w, int h, int scale)
{
	if(m) paths = get_random_paths(paths, n, m);
	data d = {0};
	d.shallow = 0;

	int i;
	d.X.rows = n;
	d.X.vals = (float**)calloc(n, sizeof(float*));
	d.X.cols = w*h*3;

	d.y.rows = n;
	d.y.vals = (float**)calloc(n, sizeof(float*));
	d.y.cols = w*scale * h*scale * 3;

	for(i = 0; i < n; ++i){
		image im = load_image_color(paths[i], 0, 0);
		image crop = random_crop_image(im, w*scale, h*scale);
		int flip = rand()%2;
		if (flip) flip_image(crop);
		image resize = resize_image(crop, w, h);
		d.X.vals[i] = resize.data;
		d.y.vals[i] = crop.data;
		free_image(im);
	}

	if(m) free(paths);
	return d;
}

data load_data_regression(char **paths, int n, int m, int k, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
{
	if(m) paths = get_random_paths(paths, n, m);
	data d = {0};
	d.shallow = 0;
	d.X = load_image_augment_paths(paths, n, min, max, size, angle, aspect, hue, saturation, exposure, 0);
	d.y = load_regression_labels_paths(paths, n, k);
	if(m) free(paths);
	return d;
}

data select_data(data *orig, int *inds)
{
	data d = {0};
	d.shallow = 1;
	d.w = orig[0].w;
	d.h = orig[0].h;

	d.X.rows = orig[0].X.rows;
	d.y.rows = orig[0].X.rows;

	d.X.cols = orig[0].X.cols;
	d.y.cols = orig[0].y.cols;

	d.X.vals = (float**)calloc(orig[0].X.rows, sizeof(float *));
	d.y.vals = (float**)calloc(orig[0].y.rows, sizeof(float *));
	int i;
	for(i = 0; i < d.X.rows; ++i){
		d.X.vals[i] = orig[inds[i]].X.vals[i];
		d.y.vals[i] = orig[inds[i]].y.vals[i];
	}
	return d;
}

data *tile_data(data orig, int divs, int size)
{
	data *ds = (data*)calloc(divs*divs, sizeof(data));
	int i, j;
	#pragma omp parallel for
	for(i = 0; i < divs*divs; ++i){
		data d;
		d.shallow = 0;
		d.w = orig.w/divs * size;
		d.h = orig.h/divs * size;
		d.X.rows = orig.X.rows;
		d.X.cols = d.w*d.h*3;
		d.X.vals = (float**)calloc(d.X.rows, sizeof(float*));

		d.y = copy_matrix(orig.y);
		#pragma omp parallel for
		for(j = 0; j < orig.X.rows; ++j){
			int x = (i%divs) * orig.w / divs - (d.w - orig.w/divs)/2;
			int y = (i/divs) * orig.h / divs - (d.h - orig.h/divs)/2;
			image im = float_to_image(orig.w, orig.h, 3, orig.X.vals[j]);
			d.X.vals[j] = crop_image(im, x, y, d.w, d.h).data;
		}
		ds[i] = d;
	}
	return ds;
}

data resize_data(data orig, int w, int h)
{
	data d = {0};
	d.shallow = 0;
	d.w = w;
	d.h = h;
	int i;
	d.X.rows = orig.X.rows;
	d.X.cols = w*h*3;
	d.X.vals = (float**)calloc(d.X.rows, sizeof(float*));

	d.y = copy_matrix(orig.y);
	#pragma omp parallel for
	for(i = 0; i < orig.X.rows; ++i){
		image im = float_to_image(orig.w, orig.h, 3, orig.X.vals[i]);
		d.X.vals[i] = resize_image(im, w, h).data;
	}
	return d;
}

data load_data_augment(char **paths, int n, int m, char **labels, int k, tree *hierarchy, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure, int center)
{
	if(m) paths = get_random_paths(paths, n, m);
	data d = {0};
	d.shallow = 0;
	d.w=size;
	d.h=size;
	d.X = load_image_augment_paths(paths, n, min, max, size, angle, aspect, hue, saturation, exposure, center);
	d.y = load_labels_paths(paths, n, labels, k, hierarchy);
	if(m) free(paths);
	return d;
}

data load_data_tag(char **paths, int n, int m, int k, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
{
	if(m) paths = get_random_paths(paths, n, m);
	data d = {0};
	d.w = size;
	d.h = size;
	d.shallow = 0;
	d.X = load_image_augment_paths(paths, n, min, max, size, angle, aspect, hue, saturation, exposure, 0);
	d.y = load_tags_paths(paths, n, k);
	if(m) free(paths);
	return d;
}

matrix concat_matrix(matrix m1, matrix m2)
{
	int i, count = 0;
	matrix m;
	m.cols = m1.cols;
	m.rows = m1.rows+m2.rows;
	m.vals = (float**)calloc(m1.rows + m2.rows, sizeof(float*));
	for(i = 0; i < m1.rows; ++i){
		m.vals[count++] = m1.vals[i];
	}
	for(i = 0; i < m2.rows; ++i){
		m.vals[count++] = m2.vals[i];
	}

    return m;
}

data concat_data(data d1, data d2)
{
	data d = {0};
	d.shallow = 1;
	d.X = concat_matrix(d1.X, d2.X);
	d.y = concat_matrix(d1.y, d2.y);
	d.w = d1.w;
	d.h = d1.h;
	return d;
}

data concat_datas(data *d, int n)
{
	int i;
	data out = {0};
	for(i = 0; i < n; ++i){
		data new = concat_data(d[i], out);
		free_data(out);
		out = new;
	}
	return out;
}

data load_categorical_data_csv(char *filename, int target, int k)
{
	data d = {0};
	d.shallow = 0;
	matrix X = csv_to_matrix(filename);
	float *truth_1d = pop_column(&X, target);
	float **truth = one_hot_encode(truth_1d, X.rows, k);
	matrix y;
	y.rows = X.rows;
	y.cols = k;
	y.vals = truth;
	d.X = X;
	d.y = y;
	free(truth_1d);
	return d;
}

data load_cifar10_data(char *filename)
{
	data d = {0};
	d.shallow = 0;
	long i,j;
	matrix X = make_matrix(10000, 3072);
	matrix y = make_matrix(10000, 10);
	d.X = X;
	d.y = y;

	FILE *fp = fopen(filename, "rb");
	if(!fp) file_error(filename);
	for(i = 0; i < 10000; ++i){
		unsigned char bytes[3073];
		fread(bytes, 1, 3073, fp);
		int class = bytes[0];
		y.vals[i][class] = 1;
		for(j = 0; j < X.cols; ++j){
			X.vals[i][j] = (double)bytes[j+1];
		}
	}
	scale_data_rows(d, 1./255);
	//normalize_data_rows(d);
	fclose(fp);
	return d;
}

void get_random_batch(data d, int n, float *X, float *y)
{
	int j;
	for(j = 0; j < n; ++j){
		int index = rand()%d.X.rows;
		memcpy(X+j*d.X.cols, d.X.vals[index], d.X.cols*sizeof(float));
		memcpy(y+j*d.y.cols, d.y.vals[index], d.y.cols*sizeof(float));
	}
}

void get_next_batch(data d, int n, int offset, float *X, float *y)
{
	int j;
	for(j = 0; j < n; ++j){
		int index = offset + j;
		memcpy(X+j*d.X.cols, d.X.vals[index], d.X.cols*sizeof(float));
		if(y) memcpy(y+j*d.y.cols, d.y.vals[index], d.y.cols*sizeof(float));
	}
}

void smooth_data(data d)
{
	int i, j;
	float scale = 1. / d.y.cols;
	float eps = .1;
	for(i = 0; i < d.y.rows; ++i){
		for(j = 0; j < d.y.cols; ++j){
			d.y.vals[i][j] = eps * scale + (1-eps) * d.y.vals[i][j];
		}
	}
}

data load_all_cifar10()
{
	data d = {0};
	d.shallow = 0;
	int i,j,b;
	matrix X = make_matrix(50000, 3072);
	matrix y = make_matrix(50000, 10);
	d.X = X;
	d.y = y;


	for(b = 0; b < 5; ++b){
		char buff[256];
		sprintf(buff, "data/cifar/cifar-10-batches-bin/data_batch_%d.bin", b+1);
		FILE *fp = fopen(buff, "rb");
		if(!fp) file_error(buff);
		for(i = 0; i < 10000; ++i){
			unsigned char bytes[3073];
			fread(bytes, 1, 3073, fp);
			int class = bytes[0];
			y.vals[i+b*10000][class] = 1;
			for(j = 0; j < X.cols; ++j){
				X.vals[i+b*10000][j] = (double)bytes[j+1];
			}
		}
		fclose(fp);
	}
	//normalize_data_rows(d);
	scale_data_rows(d, 1./255);
	smooth_data(d);
	return d;
}

data load_go(char *filename)
{
	FILE *fp = fopen(filename, "rb");
	matrix X = make_matrix(3363059, 361);
	matrix y = make_matrix(3363059, 361);
	int row, col;

	if(!fp) file_error(filename);
	char *label;
	int count = 0;
	while((label = fgetl(fp))){
		int i;
		if(count == X.rows){
			X = resize_matrix(X, count*2);
			y = resize_matrix(y, count*2);
		}
		sscanf(label, "%d %d", &row, &col);
		char *board = fgetl(fp);

		int index = row*19 + col;
		y.vals[count][index] = 1;

		for(i = 0; i < 19*19; ++i){
			float val = 0;
			if(board[i] == '1') val = 1;
			else if(board[i] == '2') val = -1;
			X.vals[count][i] = val;
		}
		++count;
		free(label);
		free(board);
	}
	X = resize_matrix(X, count);
	y = resize_matrix(y, count);

	data d = {0};
	d.shallow = 0;
	d.X = X;
	d.y = y;


	fclose(fp);

	return d;
}


void randomize_data(data d)
{
	int i;
	for(i = d.X.rows-1; i > 0; --i){
		int index = rand()%i;
		float *swap = d.X.vals[index];
		d.X.vals[index] = d.X.vals[i];
		d.X.vals[i] = swap;

		swap = d.y.vals[index];
		d.y.vals[index] = d.y.vals[i];
		d.y.vals[i] = swap;
	}
}

void scale_data_rows(data d, float s)
{
	int i;
	for(i = 0; i < d.X.rows; ++i){
		scale_array(d.X.vals[i], d.X.cols, s);
	}
}

void translate_data_rows(data d, float s)
{
	int i;
	for(i = 0; i < d.X.rows; ++i){
		translate_array(d.X.vals[i], d.X.cols, s);
	}
}

data copy_data(data d)
{
	data c = {0};
	c.w = d.w;
	c.h = d.h;
	c.shallow = 0;
	c.num_boxes = d.num_boxes;
	c.boxes = d.boxes;
	c.X = copy_matrix(d.X);
	c.y = copy_matrix(d.y);
	return c;
}

void normalize_data_rows(data d)
{
	int i;
	for(i = 0; i < d.X.rows; ++i){
		normalize_array(d.X.vals[i], d.X.cols);
	}
}

data get_data_part(data d, int part, int total)
{
	data p = {0};
	p.shallow = 1;
	p.X.rows = d.X.rows * (part + 1) / total - d.X.rows * part / total;
	p.y.rows = d.y.rows * (part + 1) / total - d.y.rows * part / total;
	p.X.cols = d.X.cols;
	p.y.cols = d.y.cols;
	p.X.vals = d.X.vals + d.X.rows * part / total;
	p.y.vals = d.y.vals + d.y.rows * part / total;
	return p;
}

data get_random_data(data d, int num)
{
	data r = {0};
	r.shallow = 1;

	r.X.rows = num;
	r.y.rows = num;

	r.X.cols = d.X.cols;
	r.y.cols = d.y.cols;

	r.X.vals = (float**)calloc(num, sizeof(float *));
	r.y.vals = (float**)calloc(num, sizeof(float *));

	int i;
	for(i = 0; i < num; ++i){
		int index = rand()%d.X.rows;
		r.X.vals[i] = d.X.vals[index];
		r.y.vals[i] = d.y.vals[index];
	}
	return r;
}

data *split_data(data d, int part, int total)
{
	data *split = (data*)calloc(2, sizeof(data));
	int i;
	int start = part*d.X.rows/total;
	int end = (part+1)*d.X.rows/total;
	data train;
	data test;
	train.shallow = test.shallow = 1;

	test.X.rows = test.y.rows = end-start;
	train.X.rows = train.y.rows = d.X.rows - (end-start);
	train.X.cols = test.X.cols = d.X.cols;
	train.y.cols = test.y.cols = d.y.cols;

	train.X.vals = (float**)calloc(train.X.rows, sizeof(float*));
	test.X.vals = (float**)calloc(test.X.rows, sizeof(float*));
	train.y.vals = (float**)calloc(train.y.rows, sizeof(float*));
	test.y.vals = (float**)calloc(test.y.rows, sizeof(float*));

	for(i = 0; i < start; ++i){
		train.X.vals[i] = d.X.vals[i];
		train.y.vals[i] = d.y.vals[i];
	}
	for(i = start; i < end; ++i){
		test.X.vals[i-start] = d.X.vals[i];
		test.y.vals[i-start] = d.y.vals[i];
	}
	for(i = end; i < d.X.rows; ++i){
		train.X.vals[i-(end-start)] = d.X.vals[i];
		train.y.vals[i-(end-start)] = d.y.vals[i];
	}
	split[0] = train;
	split[1] = test;
	return split;
}
#undef class
#undef new
